Burn The Map

Crazy ones? You're damn right.Burn the Map is a podcast about the people who can't help but chase obsession. Before the exits. Before the followers. Before anyone asked them to. These are deep-dive interviews with innovators, artists, hackers, tinkerers—people whose dedication to their craft borders on lunacy. We dissect the nuance of what they do, what keeps them going, and why their work matters.Hosted by Dan Baird, this show is a guided tour into the minds of people who do the work that seems illogical—until it isn't.

Burn The Map is a business podcast hosted by Dan Baird, with 42 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Dan Baird hosts Burn The Map, a business show with 42 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #40

  Burn The Map: AI, Brain Science, and the Future of Longevity with Andrea Olsen

  Aug 27, 202653 minS1

  In This Episode: We talk to Andrea Olsen about what happens when neuroscience, machine learning, and longevity research stop being separate lanes and start crashing into each other. Andrea is studying computational neural systems, building Luria Health, and thinking way beyond the usual "AI in healthcare" clichés. We get into brain-computer interfaces, digital twins, occupational health, lucid dreaming, memory hacks, and the very real possibility that the future of medicine looks a lot more personalized—and a lot less dumb. If you've ever wondered what it looks like when someone is equally obsessed with the brain, the body, and the systems we use to keep both alive, this one delivers. What We Cover: How Andrea ended up at the intersection of neuroscience, machine learning, and business. Why brain-computer interfaces could change life for people with paralysis, sensory loss, and cognitive injury. The difference between generic AI hype and building medical systems that doctors might actually trust. How Luria Health is using AI to predict and prevent emergencies in high-risk work environments. What longevity "escape velocity," digital twins, and even digitized consciousness could mean in practice. Guest Bio: Andrea Olsen is a computational neural systems student, neuroscience researcher, and founder of Luria Health. Her work sits at the edge of brain science, AI, occupational medicine, and longevity—spanning everything from BCIs and medical copilots to personalized health systems designed to predict problems before they become disasters. She's also contributed to conversations around moonshot health innovation through XPRIZE and brings the kind of curiosity that tends to make normal people feel under-caffeinated. Enjoy the episode. This show is brought to you by Wrench.ai . Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird Follow Andrea: LinkedIn: https://www.linkedin.com/in/andrea-olsen-0987654321/ Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPod Instagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social Selected Links From This Episode: Luria Health: https://luria.health Wrench.ai: https://wrench.ai Caltech XPRIZE Insilico Medicine PubMed People and Organizations Mentioned: Andrea Olsen Dan Baird Luria Health Caltech XPRIZE Peter Diamandis David Sinclair Jamie Justice Alex Zhavoronkov Insilico Medicine Neuralink Science Corp OpenAI Shapiro Lab Wrench.ai Show Notes & Timestamps: 00:08 — Andrea's academic stack: computational neural systems, neuroscience, and business 01:05 — How machine learning borrows from the brain 03:08 — Brain-computer interfaces, paralysis, and giving people "superpowers" 04:33 — Why invasive neural implants are still so difficult 05:49 — Ultrasound, Neuralink, and where BCI research is heading 07:08 — What pulled Andrea into neuroscience in the first place 10:02 — Memory palaces, dyslexia, and the startup idea she almost built 10:57 — Andrea's early AI work helping children with dyslexia and aphasia 11:52 — GANs explained simply 14:34 — Longevity Brain Lab and solving math problems during workouts 17:30 — Novelty, new stimuli, and changing your perception of time 19:07 — How Andrea got involved with XPRIZE 21:31 — The moonshot idea: digitizing consciousness 22:46 — Longevity escape velocity and the dream of outrunning death 23:20 — David Sinclair, vision restoration, and Yamanaka factors 28:26 — Glioblastoma, hard problems, and why Andrea chose to work on them 30:06 — Fasting, ketosis, and brain clarity 31:20 — Lucid dreaming, dream control, and sleep experimentation 35:24 — What Luria Health actually does 39:39 — Building a doctor copilot for occupational medicine 41:55 — The long-term vision: a personal longevity concierge 42:46 — Why generic LLMs shouldn't be trusted with your health 46:05 — How the medical training data is structured 50:38 — Where to find Andrea and what's live now 51:19 — Who she follows, learns from, and recommends

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  Episode #39

  Burn The Map: Don't Mistake AI Fluency for Understanding w/ Dr. Anastassia Lauterbach

  Aug 20, 20261h 5mS1

  In This Episode: We talk to D. Anastassia Lauterbach about what it actually takes to think clearly about AI when everyone else is either panicking, posturing, or treating it like magic. She brings a rare mix of operator experience, board-level governance perspective, and deep curiosity about how AI will reshape business, education, and society. We get into why AI literacy matters more than hype, what leaders keep getting wrong about adoption, and why understanding the limits of these systems is just as important as understanding their potential. If there's a throughline here, it's this: the future belongs to people who can engage with AI seriously, not just loudly. What We Cover: Why AI literacy matters more than shallow tool fluency. How business leaders should think about AI governance, risk, and real adoption. The gap between AI hype and what these systems can actually do. Why education, critical thinking, and human judgment still matter more than ever. How Anastassia thinks about the long game for AI, business, and society. Guest Bio: D. Anastassia Lauterbach is a technology strategist, founder, author, and board director focused on artificial intelligence, cybersecurity, and corporate governance. She is the founder and CEO of AI Edutainment and has served in senior leadership and board roles across global technology and business organizations, including Qualcomm, Deutsche Telekom, easyJet, and Dun & Bradstreet. She is the author of The Artificial Intelligence Imperative and has taught and spoken widely on AI, innovation, and responsible technology. Enjoy the episode. This show is brought to you by Wrench.ai . Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird Follow Dr. Lauterbach: LinkedIn: https://www.linkedin.com/in/dr-anastassia-lauterbach-021a004/ Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPod Instagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social Selected Links From This Episode: Romy & Roby on Amazon AI Edutainment: https://www.aiedutainment.ai AI Snacks with Romy and Roby Wrench.ai: https://wrench.ai People and Organizations Mentioned: Andrew Ng Yann LeCun Jürgen Schmidhuber Judea Pearl Stephen Wolfram Sam Altman DeepMind Anthropic OpenAI Meta Deutsche Telekom House of Lords Show Notes & Timestamps: 01:01 — Anastassia's path: computational linguistics, immigration, big tech, and education 03:35 — Why AI hype exploded—and why most companies still don't understand the fundamentals 05:32 — AI literacy vs. AI fluency, and the House of Lords initiative 06:20 — What people get wrong about LLMs, reasoning, and consciousness 08:00 — Causality, counterfactuals, and why today's AI still falls short 10:05 — World models, human learning, and what machines still can't do well 11:43 — Theory of mind, chimpanzees, and the alignment problem 14:43 — Chinese open-weight models, cost advantages, and practical business use cases 18:10 — What Anastassia thinks Europe got wrong with the AI Act 21:47 — Synthetic data, bias, and copies of copies of copies 24:16 — Why "unbiased AI" is a fantasy 25:10 — AI as electricity—and why people still need to understand how it works 28:29 — Hallucinations, legal risk, and why narrow use cases matter 31:09 — Will AI widen the gap between the excellent and the passive? 34:34 — Why students want AI leadership and teachers often don't provide it 38:59 — Agentic workflows, governance, and the need for auditability 42:14 — GPU compute, CAPEX risk, and the hidden economics of AI infrastructure 49:14 — Personalized learning, education infrastructure, and what AI should actually improve 52:21 — What kids need most: applied math, writing, and disciplined skill-building 01:00:04 — Romy & Roby, where to find Anastassia, and what she's building next

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  Episode #38

  Burn The Map: Branding That Converts in the Age of AI w/ Kate DiLeo

  Aug 7, 202650 minS1

  In This Episode: We talk to Kate DiLeo about why you can't just prompt your way into a brand people actually care about. Kate breaks down the difference between cranking out content and building messaging that genuinely moves people to act. She walks through how she rebuilt her business for the AI era without turning herself into a SaaS founder, why so many companies end up with bland, forgettable positioning after letting ChatGPT take the wheel, and why the real edge still comes from human judgment, clear methodology, and a deep understanding of how people make decisions. If your brand sounds fine but isn't converting, this one will hit a nerve. What We Cover: Why AI-generated messaging so often turns into polished vanilla mush. The difference between "making content" and actually building a brand. How Kate compressed her branding process from multi-week workshops into faster, smarter AI-assisted sprints. Why tone of voice, ICP clarity, and differentiated messaging still have to start with human strategy. The brand metrics that actually matter—like sales-cycle compression, better-fit prospects, and faster movement from homepage to product page. Guest Bio: Kate DiLeo is a brand strategist, speaker, and messaging expert who helps B2B companies build brands that drive revenue. She's the creator of the Brand Trifecta methodology, a framework built to help companies clarify what they do, why it matters, and how to say it in a way that actually converts. With a background that blends marketing, sales, and linguistic anthropology, Kate brings a rare mix of strategic rigor and real-world practicality to the messy work of brand building. Enjoy the episode. This show is brought to you by Wrench.ai . Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird Follow Kate: LinkedIn: https://www.linkedin.com/in/katedileo/ Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPod Instagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social Selected Links From This Episode: Burn The Map: https://burnthemapshow.com/ Wrench.ai: https://wrench.ai People and Organizations Mentioned: Kate DiLeo Dan Baird Wrench.ai Claude ChatGPT HubSpot ConAgra Lovesac Pavilion Inbound Show Notes & Timestamps: 00:08 — Dan opens with why the best podcast conversations start with genuine curiosity 01:12 — AI gets good enough to feel spooky: the white-collar "my job can be orchestrated" moment 03:55 — Kate on why AI-generated brand messaging keeps turning into beige sludge 06:05 — Kate's abandoned SaaS build, sunk costs, and the lesson that changed her business model 08:25 — Rebuilding a 10-year brand strategy business for faster, cheaper, AI-assisted delivery 10:33 — From Google Docs to markdown files: the new output clients actually want 11:16 — Dan on why people pay for judgment, not just production 12:06 — "Brand creates conversations that convert": Kate defines what branding is actually for 14:41 — The psychology of messaging and why language can't be separated from human behavior 18:06 — AI burnout, innovation fatigue, and the cost of building from FOMO 20:25 — Why businesses should stay in their zone of excellence instead of chasing every new tool 24:18 — Niche harder: why clearer positioning matters even more in the AI search era 29:29 — Why the old elevator pitch is broken—and what should replace it 32:10 — Kate's early sales career, DISC training, and the communication lesson that shaped her brand work 33:30 — Why aspirational branding fails and authenticity still wins 39:32 — Schtick vs. methodology: what actually gets you taken seriously 42:16 — The brand KPIs Kate actually trusts: homepage conversion, speed to product page, sales-cycle compression 47:48 — The simplest summary: strategy first, then AI

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  Episode #37

  Burn The Map: Turning AI Into Operational Leverage w/ Brad Groux

  Jul 30, 20261h 1mS1

  In This Episode: We talk to Brad Groux about practical AI, automation, and the gap between flashy demos and systems that actually survive real work. As Co-Founder and CEO of Digital Meld, Brad operates like a builder first: cloud, workflow, Microsoft integrations, agent orchestration, and the messy reality of getting AI to do useful things inside a business. We get into his obsession with making AI operational instead of ornamental, why most teams are chasing optics instead of outcomes, and how his work across Digital Meld, OpenClaw, and Veritas Kanban reflects a bigger belief: the future belongs to people who can turn complexity into working systems. What We Cover: Why most AI rollouts fail in practice: no workflow, no context, no operational backbone. The difference between talking about automation and actually shipping it inside a business. What Brad learned building in public across Digital Meld, OpenClaw's Microsoft ecosystem work, and Veritas Kanban. Why local-first, inspectable, hands-on systems matter more than polished AI theater. How operators can use AI for operations, decision support, data pipelines, and business intelligence without drowning in hype. Guest Bio: Brad Groux is the Co-Founder and CEO of Digital Meld, where he focuses on AI and automation architecture, workflow definition, Microsoft integration, and product direction. He hosts the Start Small, Think Big podcast with Digital Meld Co-Founder and CTO Robert Groux, covering practical AI, automation, data, analytics, and process improvement. Brad has also been publicly identified as a Microsoft maintainer and liaison for OpenClaw, and he builds in public through projects like Veritas Kanban, a local-first task management and orchestration tool for people working with AI agents. Enjoy the episode. This show is brought to you by Wrench.ai . Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird Follow Brad: LinkedIn: https://www.linkedin.com/in/bradgroux/ Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPod Instagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social Selected Links From This Episode: Digital Meld: https://digitalmeld.io/about Brad Groux on GitHub: https://github.com/bradgroux OpenClaw: https://openclaw.ai Peter Steinberger on OpenClaw and the future: https://steipete.me/posts/2026/openclaw Veritas Kanban: https://github.com/BradGroux/veritas-kanban Start Small, Think Big on Apple Podcasts: https://podcasts.apple.com/us/podcast/start-small-think-big-a-podcast-and-newsletter/id1802232903 People and Organizations Mentioned: Brad Groux Dan Baird Digital Meld OpenClaw Peter Steinberger Microsoft GitHub Anthropic OpenAI HubSpot Houston AI Club World Affairs Council of Greater Houston Wrench.ai Show Notes & Timestamps: 00:08 — Brad's role at Digital Meld and why five-to-ten-year planning now feels more like five-to-ten-day planning 00:21 — Joining the OpenClaw team and working with Peter Steinberger 00:57 — Bringing agentic AI into Microsoft and the enterprise without handing it the keys to the kingdom 01:29 — Why AI has already changed Brad's business model 02:13 — The existential question: what happens when the tool can do your job? 03:15 — OpenClaw's speed, scale, and what one obsessed builder can now do 04:22 — Building clickable demos during live client calls 08:39 — Don't marry the model: foundations over hype 09:30 — Why Brad teaches SOPs and PRDs before tools 10:35 — "This is the first technology that teaches you how to use it" 11:49 — What actually matters in multi-agent architecture 13:07 — Why letting agents run wild is usually user error, not AI magic gone wrong 15:59 — How Digital Meld works with mid-market companies and where automation starts 17:52 — Talk to the people doing the work, not the exec who heard about AI on a golf course 19:22 — Cron jobs, daily briefings, and Brad's personal operating system 21:33 — Building "brainmail" and creating a shared source of truth across humans and agents 24:39 — Why building in public is becoming a serious career advantage 30:17 — Verification, hallucinations, and the feeling that labs keep moving the goalposts 31:31 — Brad's frustrations with Anthropic and why portability matters 37:41 — Brad's side projects, command center, and open-source workflow tools 38:31 — Why he built his own CRM instead of renewing HubSpot 45:43 — Why most big-company leaders aren't smarter — just higher up the org chart 50:40 — Optimism, accountability, and the need to build a future that isn't dictated by a handful of labs 55:35 — Decentralization, bad actors, and why apathy is the real enemy 58:55 — Where to find Brad and who he thinks is worth following

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  Episode #36

  Burn The Map: The Real Cost of Shipping AI Without Guardrails w/ Gabriela Bar

  Jul 23, 202650 minS1

  In This Episode: We talk to Gabriela Bar about why AI governance is no longer a side conversation for lawyers and compliance people—it's becoming the dividing line between products that actually deserve trust and products that are basically theater. Gabriela breaks down what businesses get wrong when they rush to say they're "using AI," why most teams still don't ask nearly enough questions about how these systems actually work, and how the European approach to regulation is trying to protect human rights without choking innovation. She also gets concrete: from GDPR and the EU AI Act to rescue robots, biased training data, black-box models, and the messy reality of building systems that are explainable to the people whose lives they affect. The throughline here is simple: if an AI system can shape access, opportunity, safety, or freedom, "trust us" is not good enough. What We Cover: Why polished AI demos often hide weak governance, vague data practices, and a lot of smoke and mirrors What GDPR, the Data Act, and the EU AI Act actually do—in plain English Why most AI systems are not classified as high-risk, and why that distinction matters How fairness, diversity, and explainability show up in real product decisions—not just policy decks What a rescue robot taught Gabriela about biased data, synthetic data, and designing for the real world Why black-box AI is still the biggest problem in high-stakes systems like healthcare, hiring, policing, and public services How Gabriela uses LLMs in legal analysis: not as an oracle, but as a sparring partner Guest Bio: Gabriela Bar is an AI lawyer and ethics advisor based in Poland who works at the intersection of emerging technology, law, governance, and trustworthy AI. She advises businesses building AI systems, IoT products, and data-driven services, helping them design for legality, transparency, and accountability from the start. She also serves as an ethics advisor on EU-funded projects, where she helps turn abstract principles like fairness, diversity, and explainability into decisions teams can actually implement. Enjoy the episode. This show is brought to you by Wrench.ai . Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird Follow Gabriela: LinkedIn: https://www.linkedin.com/in/gabrielabar/ Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPod Instagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social Selected Links From This Episode: Burn The Map: https://burnthemapshow.com/ Wrench.ai: https://wrench.ai People and Organizations Mentioned: Gabriela Bar Dan Baird Wrench.ai European Union Google Microsoft OpenAI Show Notes & Timestamps: 00:09 — Poland, Europe, and why this conversation matters now 01:53 — Dan's thesis: AI governance may be one of the most future-proof jobs in tech 04:03 — Why sign-off, accountability, and human responsibility aren't going away 06:24 — Gabriela on why teams need to interrogate AI products, not admire the packaging 07:02 — The problem with polished tools that can't explain where data is stored or how decisions are made 10:04 — A plain-English walkthrough of GDPR, the Data Act, and the EU AI Act 13:10 — What "high-risk AI" actually means and why most tools may not fall into that category 14:10 — Social scoring, surveillance, and the kinds of AI practices Europe is trying to stop 16:39 — Innovation versus restraint: should democracies regulate while competitors race ahead? 19:17 — What Gabriela's clients actually hire her to do 22:04 — Advising EU-funded projects and building ethics into AI from day one 24:40 — A rescue robot case study: fairness, diversity, and why training data can fail in the real world 28:47 — Why transparency and explainability depend on who needs the explanation 31:25 — The difference between ethics as a checkbox and ethics as an operating principle 34:29 — Why many companies still treat AI implementation like theater 37:22 — The AI ethics community's biggest concern: black-box decision making in high-stakes systems 40:20 — Explainable AI, practical accountability, and what users actually need to know 44:10 — How Gabriela uses LLMs in legal analysis and structured debate 47:08 — Which tools she avoids, and why data jurisdiction still matters 48:32 — Why she doesn't follow a single guru and prefers diverse sources of information 49:13 — Where to find Gabriela and follow her work

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